The problem of allocating resources over time to different demands in a "fair" way, is present in many application domains. If the resource can be allocated with an arbitrarily fine granularity at no cost, then any type of resource allocation can be achieved (we call this scheme fluid for its resemblance to water). Instead, if the resource has some coarse granularity, then the fluid resource allocation can only be approximated. The notion of lag measures the distance between the fluid schedule and the real schedule which can be actually achieved.

In this presentation, we illustrate the Adaptive Fair Schedule (AFS), which is capable to achieve a bounded lag in presence of time overhead, and uncertainties in the resource allocation. Thanks to its generality, AFS can be applied to many different application domains including: reconfigurable computing, multiprocessor scheduling, and thermal management.

Enrico Bini is Associate Professor at Università di Torino, Dept. of Computer Science. Until very recently, he was Assistant Professor at Scuola Superiore Sant'Anna (Real-Time Systems Lab) in Pisa. Also, in 2012-14 he was Marie-Curie fellow at Lund University, Dept. of Automatic Control. In 2004, he received the PhD on Real-Time Systems at Scuola Superiore Sant'Anna (recipient of the "Spitali Award" for best PhD thesis of the whole university). In January 2010 he also completed a Master degree in Mathematics with a thesis on optimal sampling for linear control systems.

He has published more than 80 papers (2 best-paper awards, 3 most cited papers @ECRTS, 2 most cited @RTSS) on real-time scheduling, resource management, and optimization methods for real-time and control systems. His service to the research community includes the participation in 55 Technical Program Committees, the review of 9 PhD thesis and about 40 papers/year, in the above mentioned research areas.